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addressing specific case studies or specific targeted techniques. The main tools to be used will come from the discipline of Machine Learning, particularly those based on Bayesian methods. The student will be
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; Midlands Graduate School Doctoral Training Partnership | Nottingham, England | United Kingdom | about 2 months ago
) challenges in measuring real-world behaviours, (ii) absence of an objective measure of pro-environmental purchasing, and (iii) lack of data on exactly when and where the intention-behaviour gap emerges within
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generative modelling, and graph neural networks. Additional responsibilities include developing research objectives and proposals; presentations and publications; assisting with teaching; liaising and
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generative modelling, and graph neural networks. Additional responsibilities include developing research objectives and proposals; presentations and publications; assisting with teaching; liaising and
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We are seeking an enthusiastic and capable individual to join our team as a PhD researcher in developing instrumentation and simulations to monitor and track satellites. The successful candidate
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modern Bayesian modelling frameworks such as Stan, Turing.jl, and PyMC, including automatic differentiation frameworks, MCMC sampling algorithms, and iterative Bayesian modelling. Special attention will be
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fluid or as individual particles; moreover, complex chemical reactions can occur between species in the plasma. Modelling a plasma is accordingly a very complex and challenging task. The objective
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for health policy decision-making, these methods will be developed using a Bayesian framework. This PhD project will deliver a substantial contribution to original research in the area of health data science
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novel multi-objective optimisation algorithms, to evaluate metrics such as material circularity, system efficiency, cost, and carbon footprint. The University of Surrey is ranked 12th in the UK in
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural